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## MODNet - Custom Portrait Video Matting Demo | |
This is a MODNet portrait video matting demo that allows you to process custom videos. | |
### 1. Requirements | |
The basic requirements for this demo are: | |
- Ubuntu System | |
- Python 3+ | |
### 2. Introduction | |
We use ~400 unlabeled video clips (divided into ~50,000 frames) downloaded from the internet to perform SOC to adapt MODNet to the video domain. **Nonetheless, due to insufficient labeled training data (~3k labeled foregrounds), our model may still make errors in portrait semantics estimation under challenging scenes.** Besides, this demo does not currently support the OFD trick. | |
For a better experience, please make sure your videos satisfy: | |
* the portrait and background are distinguishable, <i>i.e.</i>, are not similar | |
* captured in soft and bright ambient lighting | |
* the contents do not move too fast | |
### 3. Run Demo | |
We recommend creating a new conda virtual environment to run this demo, as follow: | |
1. Clone the MODNet repository: | |
``` | |
git clone https://github.com/ZHKKKe/MODNet.git | |
cd MODNet | |
``` | |
2. Download the pre-trained model from this [link](https://drive.google.com/file/d/1Nf1ZxeJZJL8Qx9KadcYYyEmmlKhTADxX/view?usp=sharing) and put it into the folder `MODNet/pretrained/`. | |
3. Create a conda virtual environment named `modnet` (if it doesn't exist) and activate it. Here we use `python=3.6` as an example: | |
``` | |
conda create -n modnet python=3.6 | |
source activate modnet | |
``` | |
4. Install the required python dependencies (please make sure your CUDA version is supported by the PyTorch version installed): | |
``` | |
pip install -r demo/video_matting/custom/requirements.txt | |
``` | |
5. Execute the main code: | |
``` | |
python -m demo.video_matting.custom.run --video YOUR_VIDEO_PATH | |
``` | |
where `YOUR_VIDEO_PATH` is the specific path of your video. | |
There are some optional arguments: | |
- `--result-type (default=fg)` : fg - save the alpha matte; fg - save the foreground | |
- `--fps (default=30)` : fps of the result video | |